Computational Approaches to Chemical Hazard Assessment

Overview

Journal ALTEX

Date 2017 Nov 5

PMID 29101769

Citations 17

Authors

Thomas Luechtefeld

Thomas Hartung

Affiliations

Soon will be listed here.

Abstract

Computational prediction of toxicity has reached new heights as a result of decades of growth in the magnitude and diversity of biological data. Public packages for statistics and machine learning make model creation faster. New theory in machine learning and cheminformatics enables integration of chemical structure, toxicogenomics, simulated and physical data in the prediction of chemical health hazards, and other toxicological information. Our earlier publications have characterized a toxicological dataset of unprecedented scale resulting from the European REACH legislation (Registration Evaluation Authorisation and Restriction of Chemicals). These publications dove into potential use cases for regulatory data and some models for exploiting this data. This article analyzes the options for the identification and categorization of chemicals, moves on to the derivation of descriptive features for chemicals, discusses different kinds of targets modeled in computational toxicology, and ends with a high-level perspective of the algorithms used to create computational toxicology models.

Citing Articles

Quantitative structure-activity relationships of chemical bioactivity toward proteins associated with molecular initiating events of organ-specific toxicity.

Gadaleta D, Garcia de Lomana M, Serrano-Candelas E, Ortega-Vallbona R, Gozalbes R, Roncaglioni A J Cheminform. 2024; 16(1):122.

PMID: 39501321 PMC: 11539312. DOI: 10.1186/s13321-024-00917-x.

Artificial intelligence (AI)-it's the end of the tox as we know it (and I feel fine).

Kleinstreuer N, Hartung T Arch Toxicol. 2024; 98(3):735-754.

PMID: 38244040 PMC: 10861653. DOI: 10.1007/s00204-023-03666-2.

Editorial: Application of computational tools to health and environmental sciences, Volume II.

Ruiz P, Loizou G Front Pharmacol. 2022; 13:1102431.

PMID: 36532722 PMC: 9751992. DOI: 10.3389/fphar.2022.1102431.

Assessment of the Effects of Chitosan, Chitooligosaccharides and Their Derivatives on .

Boros B, Dascalu D, Ostafe V, Isvoran A Molecules. 2022; 27(18).

PMID: 36144862 PMC: 9502776. DOI: 10.3390/molecules27186123.

Multi-Strategy Assessment of Different Uses of QSAR under REACH Analysis of Alternatives to Advance Information Transparency.

Chinen K, Malloy T Int J Environ Res Public Health. 2022; 19(7).

PMID: 35410019 PMC: 8998180. DOI: 10.3390/ijerph19074338.

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